Project Background

Temperatures are rising rapidly at the global scale due to the release of greenhouse gasses (IPCC, 2021). It is of the utmost importance to quantify how sensitive the climate system is to increased greenhouse gases. If we better constrain how much a gigaton of CO2 released to the atmosphere will increase air temperatures, we can more effectively mitigate future climate and environmental changes.

Constraining the climate of the past is our best way to determine the sensitivity of the climate system to changes in greenhouse gasses. Past climate can be quantified if we know, for example, the size and shape of ancient glaciers. Deposits of loose rock left behind by ancient glaciers, also called moraines, preserve the shape of these past glaciers and are abundant across the American West. Classic examples of glacial moraines can be found at the mouths of Little Cottonwood and Bells Canyons.

While many efforts have used single moraines to constrain past climate, the full potential of the moraine record to estimate climate sensitivity has not yet been realized. The primary issue limiting the use of the moraine record is the lack of comprehensive ancient glacier outlines. To solve this bottleneck we are creating the first standardized paleoglacier outline dataset at the continental scale. This will allow for the efficient estimation of climate sensitivity using automated glacier models. We are using the Western US as a test case, after which we intend to apply the method globally.

Modern glaciers are also contracting rapidly in response to climate change. A second focus of this opportunity is the documentation of the ongoing changes to glaciers covered with loose rock in the Wasatch Range.

Student Role

The student selected for this project will engage a range of methods related to glaciers in the past, present, and future. Depending on the selected student's interest the day-to-day tasks will be adjusted to keep the work engaging and interesting throughout the summer program. A primary focus will be using high resolution satellite and topographic data products to draw ancient glacier outlines. The student will learn to use Geographical Information System (GIS) programs and Google Earth. Optional: if the selected student is interested in learning to write computer code or is already familiar, opportunities are available in code development and modeling.

The student will also have the option to engage in field work every week related to glaciers past and present. In the field, students will for example: (1) use a state-of-the-art GPS to measure glacier velocities at high resolution on Timpanogos Glacier, (2) install meteorological instruments; and/or (3) conduct geophysical surveys in the Wasatch Range.

The student researcher will also have the option to learn how to determine the age of glacial deposits using the cosmogenic nuclide 3-helium. In the lab, students would learn to (1) crush rocks; (2) separate minerals; and (3) use a mass spectrometer.

A typical week could have the student mixing the interpretation of satellite imagery, using a mass spectrometer, and hiking in the Wasatch to make geophysical measurements. No prior experience in the computer programs, field work, or laboratory work is required.

Student Learning Outcomes and Benefits

Modern STEM research requires a high degree of flexibility in thought and skill. The student researcher will be empowered to develop their own research question that aligns with their personal interests and the broader project. Through this mentored process the student will reflect on their personal preferences, the literature, and available methods.

A range of opportunities for skill development will be offered. The student researcher could engage in computer, field, and/or laboratory work. By exposing the student to a range of methods they will also learn which methods they personally connect with. This will be invaluable as the student hones their interests for the next steps in their career beyond the University of Utah.

The rapid pace of technological innovation means that the types of data available for research are rapidly evolving. This project will develop the student's ability to use cutting edge remote sensing datasets and data analysis programs. The student researcher will also be given the option of learning to write code using the programing language Python. Learning to code can open a range of career opportunities at private data science companies or in academic STEM fields.

The student will develop collaborative skills by working within a cohort of undergraduates working on similar topics. The student's work will contribute into larger efforts that lead to scientific publications and connect to work ongoing at other universities and the United States Geological Survey.